SKILLEMALL.ai
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BC macos-cleaner

Analyze and reclaim macOS disk space through intelligent cleanup recommendations. This skill should be used when users report disk space issues, need to clean up their Mac, or want to understand what's consuming storage. Focus on safe, interactive analysis with user confirmation before any deletions.

ClawHub Agent Skills author: wusuiling-if v1.0.0 MIT-0 11 files body ≈ 8 873 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process C 53/100 · Has gaps — weak spots: result and completion, inputs and preconditions, consistency

AnalyzerInfrastructureData and analyticstype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
B
83/100
safety, quality, tests
Safety 60%
85
Quality 40%
79
Run on models
none yet
Process rating
C
53/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Consistency w 8
40
the three weakest of ten parameters · all ten

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Dangerous commands medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The skill contains commands that delete files, rewrite disks or execute code fetched from the network. The agent may run them without asking if it believes the instructions require it.

For the author

Replace destructive commands with safe equivalents that ask for confirmation, scope them to one folder, and stop piping curl into a shell: pin a version and a checksum.

How to improve

  1. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
For the model run — optional
  • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
  • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

Guard findings · 3

✓ No critical or high findings

Medium and low: 3
  • medium Dangerous commands cmd-privilege references/cleanup_targets.md:42
    Privilege escalation / world-writable permissions
    sudo rm -rf /Library/Caches/*
  • medium Dangerous commands cmd-privilege references/safety_rules.md:170
    Privilege escalation / world-writable permissions
    sudo rm -rf /Library/Caches/*
  • medium Dangerous commands cmd-privilege SKILL.md:1089
    Privilege escalation / world-writable permissions
    sudo rm -rf /Library/Caches/*

Files scanned: 11. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning body-long SKILL.md body ≈ 8873 tokens (recommended < 5000); move details to references/

Process rating: all ten parameters 53/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 40Consistency. Frontmatter name (macos-cleaner) differs from the folder (macos-disk-cleaner)
  • 40Execution cost. Instruction body is 8873 tokens: crowds the task out of the window
  • 50When it triggers. No condition that starts the skill
  • 60Tools and files. Uses tools (bash, python, node) that frontmatter does not declare
  • 100Steps. 110 steps
  • 100Failures and branches. 2 branches, has a failure section
  • 100Running it twice. Mutating operations check current state
  • 100Progress reporting. Reports progress
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 20 top-level sections: this looks like several domains in one skill

Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

Quality signals

  • +5Description has no quoted example phrases that should trigger the skill
  • +4Description does not say when NOT to use the skill (false activations)
  • +3Output format is not stated: the model decides each time
  • -231 emoji in the instructions: noise for the model
  • +1No license
  • +2Single-language instructions
  • +3Description length 301: enough signal without eating the budget
  • +4Structure: 59 headings
  • +3Step-by-step instructions: 110 items
  • +4Has examples (46 code blocks)
  • +4Reference files are cited in the instructions (3 of 3)
  • +3All 6 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 79.

External checks

ClawHub: suspicious
This macOS cleanup skill is mostly on-purpose, but it needs Review because it can permanently delete broad local paths and gives risky cleanup commands with inconsistent safeguards.
LLM: suspicious (high) · VirusTotal: · 29 May 2026